Abstract

Tissue clearing is one of the most powerful strategies for a comprehensive analysis of disease progression. Here, we established an integrated pipeline that combines tissue clearing, 3D imaging, and machine learning and applied to a mouse tumour model of experimental lung metastasis using human lung adenocarcinoma A549 cells. This pipeline provided the spatial information of the tumour microenvironment. We further explored the role of transforming growth factor-β (TGF-β) in cancer metastasis. TGF-β-stimulated cancer cells enhanced metastatic colonization of unstimulated-cancer cells in vivo when both cells were mixed. RNA-sequencing analysis showed that expression of the genes related to coagulation and inflammation were up-regulated in TGF-β-stimulated cancer cells. Further, whole-organ analysis revealed accumulation of platelets or macrophages with TGF-β-stimulated cancer cells, suggesting that TGF-β might promote remodelling of the tumour microenvironment, enhancing the colonization of cancer cells. Hence, our integrated pipeline for 3D profiling will help the understanding of the tumour microenvironment.

Shimpei Kubota et al. describe a pipeline for quantitative whole-organ analysis that that combines tissue clearing, 3D imaging, and machine learning for analysis of the tumour microenvironment. The authors apply this in a mouse model of lung tumour and reveal the role of TGF-β in remodelling the cellular microenvironment favouring metastatic invasion.

Details

Title
Whole-organ analysis of TGF-β-mediated remodelling of the tumour microenvironment by tissue clearing
Author
Kubota, Shimpei I 1 ; Takahashi, Kei 1 ; Mano Tomoyuki 2 ; Matsumoto Katsuhiko 3 ; Katsumata Takahiro 2 ; Shi Shoi 2 ; Tainaka Kazuki 4 ; Ueda, Hiroki R 5   VIAFID ORCID Logo  ; Ehata Shogo 6   VIAFID ORCID Logo  ; Miyazono Kohei 1   VIAFID ORCID Logo 

 The University of Tokyo, Department of Molecular Pathology, Graduate School of Medicine, Tokyo, Japan (GRID:grid.26999.3d) (ISNI:0000 0001 2151 536X) 
 The University of Tokyo, Department of Systems Pharmacology, Graduate School of Medicine, Tokyo, Japan (GRID:grid.26999.3d) (ISNI:0000 0001 2151 536X) 
 RIKEN Quantitative Biology Center, Laboratory for Synthetic Biology, Osaka, Japan (GRID:grid.508743.d) 
 Niigata University, Brain Research Institute, Niigata, Japan (GRID:grid.260975.f) (ISNI:0000 0001 0671 5144) 
 The University of Tokyo, Department of Systems Pharmacology, Graduate School of Medicine, Tokyo, Japan (GRID:grid.26999.3d) (ISNI:0000 0001 2151 536X); RIKEN Quantitative Biology Center, Laboratory for Synthetic Biology, Osaka, Japan (GRID:grid.508743.d) 
 The University of Tokyo, Department of Molecular Pathology, Graduate School of Medicine, Tokyo, Japan (GRID:grid.26999.3d) (ISNI:0000 0001 2151 536X); The University of Tokyo, Environmental Science Center, Tokyo, Japan (GRID:grid.26999.3d) (ISNI:0000 0001 2151 536X) 
Publication year
2021
Publication date
2021
Publisher
Nature Publishing Group
e-ISSN
23993642
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2497363320
Copyright
© The Author(s) 2021. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.